一种新的基于神经网络的电力系统谐波检测方法研究

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Abstract The widespread application of power-electronic loads has led to increasing harmonic pollution in power system. Harmonic detection is considered the most crucial part for preventing the influence of harmonic. In this paper, an effective procedure based on radial basis function neural network has been proposed to detect the amplitude and phase of harmonic. By comparing with BP neural network by using Matlab simulation, it is shown that the presented solution has more accurate and less training time, so it could be applied in power system harmonic detection.

Key words： BPN RBFNN harmonic detection Matlab simulation

Received: 11 October 2013 Published: 22 May 2014

PACS:

TM711

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	Articles by authors
	Xiao Jianping
	Li Shenghu
	Wu Kehan
	He Yigang

Cite this article:

Xiao Jianping,Li Shenghu,Wu Kehan等. A Novel Approach of Harmonic Detection in Power System Based on Neural Network[J]. Transactions of China Electrotechnical Society, 2013, 28(2增): 345-348.

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http://dgjsxb.ces-transaction.com/EN/ OR http://dgjsxb.ces-transaction.com/EN/Y2013/V28/I2增/345

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作者简介:肖建平男, 1988年生, 硕士研究生, 研究方向为电能质量、电力系统谐波分析。李生虎男, 1974年生, 教授, 博士生导师, 研究方向为电力系统运行与控制、柔性输电等。